Mechanisms for slow strengthening in granular materials

Several mechanisms cause a granular material to strengthen over time at low applied stress. The strength is determined from the maximum frictional force F_max experienced by a shearing plate in contact with wet or dry granular material after the layer has been at rest for a waiting time \tau. The layer strength increases roughly logarithmically with \tau -only- if a shear stress is applied during the waiting time. The mechanisms of strengthening are investigated by sensitive displacement measurements and by imaging of particle motion in the shear zone. Granular matter can strengthen due to a slow shift in the particle arrangement under shear stress. Humidity also leads to strengthening, but is found not to be its sole cause. In addition to these time dependent effects, the static friction coefficient can also be increased by compaction of the granular material under some circumstances, and by cycling of the applied shear stress.Comment: 21 pages, 11 figures, submitted to Phys. Rev.

What are the required elements needed to create an effective visual art intervention for people with dementia? A qualitative exploration

Background: This paper aims to advance understanding of ‘what works’ in visual art interventions from the perspective of key stakeholders’, including people with dementia, their family members and visual art professionals. Method: Semi-structured interviews were conducted with 22 participants, exploring their perceptions on barriers, facilitators, perceived benefits, experiences of delivering/attending a visual art intervention, and any recommendations for implementation. Results: Five factors were identified within the interviews that indicated important considerations for intervention structure and implementation, including: benefits of group work, a skilled facilitator, participant choice, artistic ability, and activity content. Whilst art therapists expressed a clear protection of professional boundaries, the success of all of the visual art interventions was largely attributed to the supportive facilitator who possessed certain core values such as empathy and compassion and had knowledge in both artistic practice and the impact of living with dementia. It was clear the group dynamic was valued, and it was important to provide enjoyable, failure-free activity content with a strong focus on the creative process. Conclusion: These findings offer a direction for evidence-based practice when implementing visual art interventions

The AuScope geodetic VLBI array

The AuScope geodetic Very Long Baseline Interferometry array consists of three new 12-m radio telescopes and a correlation facility in Australia. The telescopes at Hobart (Tasmania), Katherine (Northern Territory) and Yarragadee (Western Australia) are co-located with other space geodetic techniques including Global Navigation Satellite Systems (GNSS) and gravity infrastructure, and in the case of Yarragadee, satellite laser ranging (SLR) and Doppler Orbitography and Radiopositioning Integrated by Satellite (DORIS) facilities. The correlation facility is based in Perth (Western Australia). This new facility will make significant contributions to improving the densification of the International Celestial Reference Frame in the Southern Hemisphere, and subsequently enhance the International Terrestrial Reference Frame through the ability to detect and mitigate systematic error. This, combined with the simultaneous densification of the GNSS network across Australia, will enable the improved measurement of intraplate deformation across the Australian tectonic plate. In this paper, we present a description of this new infrastructure and present some initial results, including telescope performance measurements and positions of the telescopes in the International Terrestrial Reference Frame. We show that this array is already capable of achieving centimetre precision over typical long-baselines and that network and reference source systematic effects must be further improved to reach the ambitious goals of VLBI2010

An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics

For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment